The DOI matches its Crossref record; 274 of the 274 references it cites were found in a registry or an index.
Structural Alert/Reactive Metabolite Concept as Applied in Medicinal Chemistry to Mitigate the Risk of Idiosyncratic Drug Toxicity: A Perspective Based on the Critical Examination of Trends in the Top 200 Drugs Marketed in the United States
Abstract
Because of a preconceived notion that eliminating reactive metabolite (RM) formation with new drug candidates could mitigate the risk of idiosyncratic drug toxicity, the potential for RM formation is routinely examined as part of lead optimization efforts in drug discovery. Likewise, avoidance of "structural alerts" is almost a norm in drug design. However, there is a growing concern that the perceived safety hazards associated with structural alerts and/or RM screening tools as standalone predictors of toxicity risks may be over exaggerated. In addition, the multifactorial nature of idiosyncratic toxicity is now well recognized based upon observations that mechanisms other than RM formation (e.g., mitochondrial toxicity and inhibition of bile salt export pump (BSEP)) also can account for certain target organ toxicities. Hence, fundamental questions arise such as: When is a molecule that contains a structural alert (RM positive or negative) a cause for concern? Could the molecule in its parent form exert toxicity? Can a low dose drug candidate truly mitigate metabolism-dependent and -independent idiosyncratic toxicity risks? In an effort to address these questions, we have retrospectively examined 68 drugs (recalled or associated with a black box warning due to idiosyncratic toxicity) and the top 200 drugs (prescription and sales) in the United States in 2009 for trends in physiochemical characteristics, daily doses, presence of structural alerts, evidence for RM formation as well as toxicity mechanism(s) potentially mediated by parent drugs. Collectively, our analysis revealed that a significant proportion (∼78-86%) of drugs associated with toxicity contained structural alerts and evidence indicating that RM formation as a causative factor for toxicity has been presented in 62-69% of these molecules. In several cases, mitochondrial toxicity and BSEP inhibition mediated by parent drugs were also noted as potential causative factors. Most drugs were administered at daily doses exceeding several hundred milligrams. There was no obvious link between idiosyncratic toxicity and physicochemical properties such as molecular weight, lipophilicity, etc. Approximately half of the top 200 drugs for 2009 (prescription and sales) also contained one or more alerts in their chemical architecture, and many were found to be RM-positive. Several instances of BSEP and mitochondrial liabilities were also noted with agents in the top 200 category. However, with relatively few exceptions, the vast majority of these drugs are rarely associated with idiosyncratic toxicity, despite years of patient use. The major differentiating factor appeared to be the daily dose; most of the drugs in the top 200 list are administered at low daily doses. In addition, competing detoxication pathways and/or alternate nonmetabolic clearance routes provided suitable justifications for the safety records of RM-positive drugs in the top 200 category. Thus, while RM elimination may be a useful and pragmatic starting point in mitigating idiosyncratic toxicity risks, our analysis suggests a need for a more integrated screening paradigm for chemical hazard identification in drug discovery. Thus, in addition to a detailed assessment of RM formation potential (in relationship to the overall elimination mechanisms of the compound(s)) for lead compounds, effects on cellular health (e.g., cytotoxicity assays), BSEP inhibition, and mitochondrial toxicity are the recommended suite of assays to characterize compound liabilities. However, the prospective use of such data in compound selection will require further validation of the cellular assays using marketed agents. Until we gain a better understanding of the pathophysiological mechanisms associated with idiosyncratic toxicities, improving pharmacokinetics and intrinsic potency as means of decreasing the dose size and the associated "body burden" of the parent drug and its metabolites will remain an overarching goal in drug discovery.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Arzneimittelforschung: Erstanwendung am Menschen in der Phase I
Miletzki, B., & Gleiter, C. H. (2005) · Bundesgesundheitsblatt Gesundheitsforsch.Gesundheitsschutz · doi:10.1007/s00103-005-1024-7 · Cited by 9,355
Membrane transporters in drug development
The International Transporter Consortium, Giacomini, K. M., Huang, S.-M., Tweedie, D. J., Benet, L. Z., Brouwer, K. L. R., Chu, X., Dahlin, A., Evers, R., Fischer, V., et al. (2010) · Nature Reviews Drug Discovery · doi:10.1038/nrd3028 · Cited by 3,340
ACETAMINOPHEN-INDUCED HEPATIC NECROSIS. IV. PROTECTIVE ROLE OF GLUTATHIONE
Mitchell, J. R., Jollow, D. J., Potter, W. Z., Gillette, J. R., & Brodie, B. B. (1973) · The Journal of Pharmacology and Experimental Therapeutics · doi:10.1016/s0022-3565(25)29666-5 · Cited by 1,737
Three Decades of β-Lactamase Inhibitors
Drawz, S. M., & Bonomo, R. A. (2010) · Clinical Microbiology Reviews · doi:10.1128/cmr.00037-09 · Cited by 1,709
Carcinogenesis by chemicals: an overview--G. H. A. Clowes memorial lecture.
MILLER, J. A. (1970) · PubMed · Cited by 1,450
N-acetyl-p-benzoquinone imine: a cytochrome P-450-mediated oxidation product of acetaminophen.
Dahlin, D. C., Miwa, G. T., Lu, A. Y., & Nelson, S. D. (1984) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.81.5.1327 · Cited by 1,078
Drug interactions with lipid-lowering drugs: Mechanisms and clinical relevance
NEUVONEN, P., NIEMI, M., & BACKMAN, J. (2006) · Clinical Pharmacology & Therapeutics · doi:10.1016/j.clpt.2006.09.003 · Cited by 859
Identification and Biological Activity of the Active Metabolite of Clopidogrel
Savi, P., Pereillo, J. M., Uzabiaga, M. F., Combalbert, J., Picard, C., Maffrand, J. P., Pascal, M., & Herbert, J. M. (2000) · Thrombosis and Haemostasis · doi:10.1055/s-0037-1614133 · Cited by 754
Anticonvulsant hypersensitivity syndrome. In vitro assessment of risk.
Shear, N. H., & Spielberg, S. P. (1988) · Journal of Clinical Investigation · doi:10.1172/jci113798 · Cited by 687
Inhibition of mitochondrial beta-oxidation as a mechanism of hepatotoxicity
Fromenty, B., & Pessayre, D. (1995) · Pharmacology & Therapeutics · doi:10.1016/0163-7258(95)00012-6 · Cited by 665
Cited by
Targeting KRAS mutant cancers with a covalent G12C-specific inhibitor
Janes, M. R., Zhang, J., Li, L.-S., Hansen, R., Peters, U., Guo, X., Chen, Y., Babbar, A., Firdaus, S. J., Darjania, L., et al. (2018) · Cell · doi:10.1016/j.cell.2018.01.006 · Cited by 1,172
Targeted Covalent Inhibitors for Drug Design
Baillie, T. A. (2016) · Angewandte Chemie International Edition · doi:10.1002/anie.201601091 · Cited by 578
Self-citationBauer, R. A. (2015) · Drug Discovery Today · doi:10.1016/j.drudis.2015.05.005 · Cited by 534
Finding the sweet spot: the role of nature and nurture in medicinal chemistry
Hann, M. M., & Keserü, G. M. (2012) · Nature Reviews Drug Discovery · doi:10.1038/nrd3701 · Cited by 411
Morgan, R. E., van Staden, C. J., Chen, Y., Kalyanaraman, N., Kalanzi, J., Dunn, R. T., Afshari, C. A., & Hamadeh, H. K. (2013) · Toxicological Sciences · doi:10.1093/toxsci/kft176 · Cited by 243
Yu, K., Geng, X., Chen, M., Zhang, J., Wang, B., Ilic, K., & Tong, W. (2014) · Drug Metabolism and Disposition · doi:10.1124/dmd.113.056267 · Cited by 150
Shah, F., Leung, L., Barton, H. A., Will, Y., Rodrigues, A. D., Greene, N., & Aleo, M. D. (2015) · Toxicological Sciences · doi:10.1093/toxsci/kfv152 · Cited by 148
Self-citationComparison of minipig, dog, monkey and human drug metabolism and disposition
Dalgaard, L. (2015) · Journal of Pharmacological and Toxicological Methods · doi:10.1016/j.vascn.2014.12.005 · Cited by 132
Alarms about structural alerts
Alves, V. M., Muratov, E. N., Capuzzi, S. J., Politi, R., Low, Y., Braga, R. C., Zakharov, A. V., Sedykh, A., Mokshyna, E., Farag, S., et al. (2016) · Green Chemistry · doi:10.1039/c6gc01492e · Cited by 133
Predicting Drug-Induced Liver Injury with Bayesian Machine Learning
Williams, D. P., Lazic, S. E., Foster, A. J., Semenova, E., & Morgan, P. (2020) · Chemical Research in Toxicology · doi:10.1021/acs.chemrestox.9b00264 · Cited by 124
The Design of Covalent Allosteric Drugs
Nussinov, R., & Tsai, C.-J. (2015) · Annual Review of Pharmacology and Toxicology · doi:10.1146/annurev-pharmtox-010814-124401 · Cited by 112
Liu, R., Yu, X., & Wallqvist, A. (2015) · Journal of Cheminformatics · doi:10.1186/s13321-015-0053-y · Cited by 92
Immune-mediated drug-induced liver injury: immunogenetics and experimental models
Gerussi, A., Natalini, A., Antonangeli, F., Mancuso, C., Agostinetto, E., Barisani, D., Di Rosa, F., Andrade, R., & Invernizzi, P. (2021) · International Journal of Molecular Sciences · doi:10.3390/ijms22094557 · Cited by 87
Erve, J. C. L., Gauby, S., Maynard, J. W., Svensson, M. A., Tonn, G., & Quinn, K. P. (2013) · Chemical Research in Toxicology · doi:10.1021/tx4001144 · Cited by 48
Essential Medicinal Chemistry of Essential Medicines
Serafini, M., Cargnin, S., Massarotti, A., Pirali, T., & Genazzani, A. A. (2020) · Journal of Medicinal Chemistry · doi:10.1021/acs.jmedchem.0c00415 · Cited by 46
Brink, A., Pähler, A., Funk, C., Schuler, F., & Schadt, S. (2017) · Drug Discovery Today · doi:10.1016/j.drudis.2016.11.018 · Cited by 42
Attwa, M. W., Kadi, A. A., & Abdelhameed, A. S. (2020) · Journal of Separation Science · doi:10.1002/jssc.201900818 · Cited by 37
Owen, K., Cross, D. M., Derzi, M., Horsley, E., & Stavros, F. L. (2012) · Regulatory Toxicology and Pharmacology · doi:10.1016/j.yrtph.2012.05.017 · Cited by 27
Metadata
- Authors
- Stepan, A. F., Walker, D. P., Bauman, J., Price, D. A., Baillie, T. A., Kalgutkar, A. S., & Aleo, M. D.
- Venue
- Chemical Research in Toxicology
- Publisher
- American Chemical Society (ACS)
- Published
- 2011-07-11
- Volume
- 24
- Issue
- 9
- Pages
- 1345-1410
- ISSN
- 0893-228X (ISSN-L)
- 1520-5010
- OpenAlex
- W2075221169
- Cited by
- 698
- References
- 274
- FWCI
- 40.51
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.